基于NSGA-Ⅱ的停机位多目标指派建模与仿真

V351.11; 为探索大型机场停机位指派问题综合现实有效的解决方法,分析了停机位指派过程设计的利益主体,以最小化航空公司运行成本、最小化旅客步行距离、最小化航班冲突概率同时最大化航空公司之间的公平性为目标,建立大型机场停机位多目标指派模型.采用第2代非支配排序遗传算法(Non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)对模型进行仿真验证,该算法可以对多目标问题进行更高效的求解.分析不同迭代次数下的Pareto前沿解集的特性,并将优化解与随机指派结果进行对比,验证了该模型和算法的有效性....

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Published in南京航空航天大学学报 Vol. 50; no. 6; pp. 823 - 828
Main Authors 徐思敏, 姜雨, 王欢, 陈丽丽
Format Journal Article
LanguageChinese
Published 南京航空航天大学民航学院,南京,211106 01.12.2018
Subjects
非支配排序遗传算法
停机位指派
Pareto前沿解
Online AccessGet full text
ISSN1005-2615
DOI10.16356/j.1005-2615.2018.06.013

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Abstract V351.11; 为探索大型机场停机位指派问题综合现实有效的解决方法,分析了停机位指派过程设计的利益主体,以最小化航空公司运行成本、最小化旅客步行距离、最小化航班冲突概率同时最大化航空公司之间的公平性为目标,建立大型机场停机位多目标指派模型.采用第2代非支配排序遗传算法(Non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)对模型进行仿真验证,该算法可以对多目标问题进行更高效的求解.分析不同迭代次数下的Pareto前沿解集的特性,并将优化解与随机指派结果进行对比,验证了该模型和算法的有效性.
AbstractList V351.11; 为探索大型机场停机位指派问题综合现实有效的解决方法,分析了停机位指派过程设计的利益主体,以最小化航空公司运行成本、最小化旅客步行距离、最小化航班冲突概率同时最大化航空公司之间的公平性为目标,建立大型机场停机位多目标指派模型.采用第2代非支配排序遗传算法(Non-dominated sorting genetic algorithm-Ⅱ,NSGA-Ⅱ)对模型进行仿真验证,该算法可以对多目标问题进行更高效的求解.分析不同迭代次数下的Pareto前沿解集的特性,并将优化解与随机指派结果进行对比,验证了该模型和算法的有效性.
Author 徐思敏
王欢
陈丽丽
姜雨
AuthorAffiliation 南京航空航天大学民航学院,南京,211106
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JIANG Yu
WANG Huan
XU Simin
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停机位指派
Pareto前沿解
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Snippet V351.11; 为探索大型机场停机位指派问题综合现实有效的解决方法,分析了停机位指派过程设计的利益主体,以最小化航空公司运行成本、最小化旅客步行距离、最小化航班冲突概率同...
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Title 基于NSGA-Ⅱ的停机位多目标指派建模与仿真
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